Modeling the power profile of mobile applications is a crucial activity to identify the causes behind energy leaks. To this aim, researchers have proposed hardware-based tools as well as model-based and software-based techniques to approximate the actual energy profile. However, all these solutions present their own advantages and disadvantages. Hardware-based tools are highly precise, but at the same time their use is bound to the acquisition of costly hardware components. Model-based tools require the calibration of parameters needed to correctly create a model on a specific hardware device. Software-based approaches do not need any hardware components, but they rely on battery measurements and, thus, they are hardware-assisted. These tools are cheaper and easier to use than hardware-based tools, but they are believed to be less precise. In this paper, we take a deeper look at the pros and cons of software-based solutions investigating to what extent their measurements depart from hardware-based solutions. To this aim, we propose a softwarebased tool named PETRA that we compare with the hardwarebased MONSOON toolkit on 54 Android apps. The results show that PETRA performs similarly to MONSOON despite not using any sophisticated hardware components. In fact, in all the apps the mean relative error with respect to MONSOON is lower than 0:05. Moreover, for 95% of the analyzed methods the estimation error is within 5% of the actual values measured using the hardware-based toolkit.
Original languageEnglish
Title of host publicationProceedings - 24th International Conference on Software Analysis, Evolution and Reengineering, SANER 2017
EditorsMartin Pinzger, Gabriele Bavota, Andrian Marcus
Place of PublicationPiscataway, NJ
Number of pages12
ISBN (Electronic)978-1-5090-5501-2
StatePublished - 2017
EventSANER 2017 - Klagenfurt, Austria


ConferenceSANER 2017

    Research areas

  • Energy Consumption, Mobile Apps, Estimation

ID: 32869554